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Dash by Plotly VS Plotly

Compare Dash by Plotly VS Plotly and see what are their differences

Dash by Plotly logo Dash by Plotly

Dash is a Python framework for building analytical web applications. No JavaScript required.

Plotly logo Plotly

Low-Code Data Apps
  • Dash by Plotly Landing page
    Landing page //
    2023-05-22
  • Plotly Landing page
    Landing page //
    2023-07-31

Dash by Plotly features and specs

  • Interactive Visualizations
    Dash by Plotly allows users to create highly interactive visualizations with ease, using a combination of Python, R, or Julia. It supports a wide variety of visualization components, which can be easily customized and stylized to the user's needs.
  • End-to-End Platform
    Dash is an end-to-end platform that covers the entire data visualization pipeline from data processing to the presentation layer. This allows users to seamlessly transition from data analysis to sharing insights without having to switch tools.
  • Open-Source
    Dash is an open-source framework, which allows for a high level of customization. It benefits from community contributions and offers transparency because users can view and modify the source code as needed.
  • Python Integration
    Dash is tightly integrated with Python, which is a major advantage for data scientists and analysts who use Python for data manipulation and analysis. It leverages the robust ecosystem of Python libraries, like Pandas and NumPy.

Possible disadvantages of Dash by Plotly

  • Limited Custom Components
    While Dash provides many components for building applications, it can sometimes be limiting when you need highly customized features or specific integrations that aren't available out of the box.
  • Learning Curve
    For users not familiar with web development concepts (like HTML, CSS, and JavaScript), Dash can have a steep learning curve because it requires understanding how web applications are structured and deployed.
  • Performance
    Dash applications can become sluggish with large datasets or highly interactive charts, as the client-side rendering can be resource-intensive. This can make it difficult to handle applications at scale without optimization.
  • Deployment Complexity
    Deploying Dash applications might be challenging, especially for users without experience in setting up servers or cloud environments. While there are services provided by Plotly for deployment, they can add extra cost and require technical setup.

Plotly features and specs

  • Interactivity
    Plotly offers highly interactive plots that allow users to pan, zoom, and hover over data points for more information. This enhances the user experience and provides deeper insights.
  • High-quality visualizations
    It provides aesthetically pleasing and highly customizable charts, making it suitable for publication-quality visuals.
  • Versatility
    Plotly supports multiple chart types including line charts, scatter plots, bar charts, and 3D plots, making it suitable for a wide range of applications.
  • Python integration
    Plotly is well-integrated with Python and works seamlessly with other popular data science libraries like Pandas, NumPy, and Scikit-learn.
  • Web-based
    The plots can be easily embedded in web applications or dashboards, making it ideal for sharing insights over the internet.
  • Open-source
    Plotly offers an open-source version, which allows users to create and share visualizations without any cost.

Possible disadvantages of Plotly

  • Performance
    Rendering very large datasets can sometimes be slow, which may not be suitable for real-time data visualization requirements.
  • Learning curve
    Even though the library is well-documented, the extensive range of features can have a steep learning curve for beginners.
  • Cost for advanced features
    While the basic functionality is free, more advanced features, such as export to certain formats and additional customizable options, require a paid subscription.
  • Dependency management
    Plotly has a number of dependencies that need to be managed properly, which can sometimes complicate the setup process.
  • Complexity
    For simple visualizations, Plotly might be overkill and simpler libraries like Matplotlib or Seaborn could be more appropriate.

Analysis of Plotly

Overall verdict

  • Overall, Plotly is a strong choice for those looking to create dynamic and interactive data visualizations, thanks to its range of features and ease of integration with web technologies.

Why this product is good

  • Plotly is considered good because it offers a comprehensive suite of tools for creating interactive visualizations that can be used in web applications, reports, and dashboards. It supports many different types of plots, is easy to use for both beginners and experienced developers, and integrates well with popular programming languages like Python, R, and JavaScript.

Recommended for

    Plotly is recommended for data scientists, analysts, and developers who need to create interactive and visually appealing data visualizations. It's particularly useful for those who work with Python or R and want the ability to embed their visualizations in web applications or dashboards.

Dash by Plotly videos

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Plotly videos

Create Real-time Chart with Javascript | Plotly.js Tutorial

More videos:

  • Review - Introducing plotly.py 3.0
  • Review - Is Plotly The Better Matplotlib?
  • Tutorial - Plotly Tutorial 2021
  • Review - Data Visualization as The First and Last Mile of Data Science Plotly Express and Dash | SciPy 2021

Category Popularity

0-100% (relative to Dash by Plotly and Plotly)
Developer Tools
100 100%
0% 0
Data Visualization
0 0%
100% 100
Productivity
100 100%
0% 0
Data Dashboard
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Dash by Plotly and Plotly

Dash by Plotly Reviews

Top 10 Tableau Open Source Alternatives: A Comprehensive List
To learn more about Plotly-Dash, you can click here to check out their official website.
Source: hevodata.com

Plotly Reviews

Best 8 Redash Alternatives in 2023 [In Depth Guide]
Plotly is specifically designed for companies who want to build and deploy analytic applications like dashboards using Python, Julia, or R without needing DevOps or Javascript developers.
Source: www.datapad.io
5 Best Python Libraries For Data Visualization in 2023
Plotly is a web-based data visualization toolkit that comes with unique functionalities such as dendrograms, 3D charts, and also contour plots, which is not very common in other libraries. It has a great API offering scatter plots, line charts, bar charts, error bars, box plots, and other visualizations. Plotly can even be accessed from a Python Notebook.
Top 8 Python Libraries for Data Visualization
Plotly is a free open-source graphing library that can be used to form data visualizations. Plotly (plotly.py) is built on top of the Plotly JavaScript library (plotly.js) and can be used to create web-based data visualizations that can be displayed in Jupyter notebooks or web applications using Dash or saved as individual HTML files. Plotly provides more than 40 unique...
5 top picks for JavaScript chart libraries
Plotly is a graphing library that’s available for various runtime environments, including the browser. It supports many kinds of charts and graphs that we can configure with a variety of options.

Social recommendations and mentions

Based on our record, Plotly seems to be a lot more popular than Dash by Plotly. While we know about 33 links to Plotly, we've tracked only 1 mention of Dash by Plotly. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Dash by Plotly mentions (1)

  • [Python] NiceGUI: Lassen Sie jeden Browser das Frontend für Ihren Python-Code sein
    Of course there are valid use cases for splitting frontend and backend technologies. NiceGUI is for those who don’t want to leave the Python ecosystem and like to reap the benefits of having all code in one place. There are other options like Streamlit, Dash, Anvil, JustPy, and Pynecone. But we initially created NiceGUI to easily handle the state of external hardware like LEDs, motors, and cameras. Additionally,... Source: about 2 years ago

Plotly mentions (33)

  • Python for Data Visualization: Best Tools and Practices
    Plotly is perfect for interactive visualizations. You can create interactive charts and graphs that allow users to hover, click, and zoom in. Plotly is also great for web-based visuals, making it easy to share your findings online. - Source: dev.to / 2 months ago
  • Generative AI Powered QnA & Visualization Chatbot
    Front End: A React application that leverages React-Chatbotify library to easily integrate a chatbot GUI. It also uses the Plotly library to display the charts/visualizations. The generative AI implementation and details are entirely abstracted from the front end. The front-end application depends on a single REST endpoint of the backend application. - Source: dev.to / 4 months ago
  • Build a Stock Dashboard in less than 40 lines of Python code!🤓
    In this tutorial, Mariya Sha will guide you through building a stock value dashboard using Taipy, Plotly, and a dataset from Kaggle. - Source: dev.to / 6 months ago
  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / 12 months ago
  • Python equivalent to power bi/power query?
    For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: over 1 year ago
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What are some alternatives?

When comparing Dash by Plotly and Plotly, you can also consider the following products

Streamlit - Turn python scripts into beautiful ML tools

D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.

Panel - High-level app and dashboarding solution for Python

Chart.js - Easy, object oriented client side graphs for designers and developers.

Streamsync - Streamsync is an open-source framework for creating data apps. Build user interfaces using a visual editor; write the backend code in Python.

RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...